Platform-to-Platform Communication - Integration Benefits for Advertisers & Publishers by Robert Schneider

PLATFORM-TO-PLATFORM COMMUNICATION:INTEGRATION BENEFITS FOR ADVERTISERS & PUBLISHERS

Robert Schneider, COO

@IngeniousTechAG

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❙Platform-to-platform communication: Integration benefits for advertisers & publishers

Topics to be covered

Exchanging Data … why talk about

it?

1) Data dimensions

2) Data sources and ownership

3) Examples and Take-

Aways

Appendix: Data tool

classification

INTRODUCTION

the bid manager's managed service within .track if you want to be specific. Perhaps that's what you meant too? - we sell it as a stand alone product.the bid manager's managed service within .track if you want to be specific. Perhaps that's what you meant too? - we sell it as a stand alone product.

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Exchanging Data … why talk about it?

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► Many players see only a fraction of the data opportunity▸ Own data is (over)protected ▸ External data is underrated or deemed unaccessible▸ Walled Gardens are increasing

► Hesitation and insecurity to exchange data with partners

► Increasing privacy and compliance concerns

► Lack of technical know-how in Online-Marketing departments

► Missing technical standards for data exchange


Introduction

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“With great power comes great

responsibility”Spiderman / Voltaire


Introduction

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Introduction

► Performance Marketing depends on responsible use of data

► Too little distinction between anonymous profiles and personally identifiable information (PII)

► Privacy on the internet discussion has reached mainstream media

► Further concerns fueled by ▸ mass surveillance ▸ massive profits by internet companies

1) DATA DIMENSIONS


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Actions, Behaviour and Personally Identifiable Information (PII) are main data dimensions

Common Data

Dimensions

ACTIONS•Customer Journey•Onsite activity•Session statistics•Conversions•Loyalty and activity index•Mostly anonymous profiles

CONTEXT• Interests• Intentions•Demographic: Age, Gender, Location

•Search Phrases•Not personally identifiable PII

•Logged-in and single sign-on profiles

•E-Mail, Phone, Address•Payment Details•Sensitive and personally identifiable

SENSITIVITY OF DATA

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Relevant data is scattered across the User Journey

Traffic Source

• User searches for product:• Search phrase CONTEXT• Interest CONTEXT• Previous searches CONTEXT• Activity history and

customised results when logged in ACTIONS PII

Publisher

• User refines decision:• Customer Journey ACTIONS • Product specifications

CONTEXT• Brand preferences CONTEXT• Price ranges CONTEXT• Session duration ACTIONS • Clicks to advertisers ACTIONS • Recommendations based on

history when logged in CONTEXT PII

Advertiser

• User purchases product:• Full personal information PII• Payment information PII• Exact product information

CONTEXT• Additional products and

purchases CONTEXT• Purchase history and lifetime

value PII

2) DATA SOURCES AND OWNERSHIP


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Data is detected or provided

► Anonymous profiles are detected▸ Created by detection algorithms and stored temporarily▸ Examples are cookies, session parameters and fingerprint algorithms▸ Sharing data is common practice, basis of tracking and analytics

► Personally identifiable profiles are provided▸ Provided by users in return for

▸ Value-added services▸ Logistics and fulfillment purposes

▸ Examples are memberships of internet platforms (Twitter, Facebook), user databases of cashback and loyalty portals, mailing lists, customer databases of online-shops (CRM, ERP)

▸ Since PII is part of the data, sharing is less common

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Side question: Are Walled Gardens ‘data heaven’? Or do big players benefit from excess

of data imports?

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Big players have created systems in which they can benefit most of all participants from data which is provided to them

► Online giants have created ‘endothermic’ systems: more data is provided to them than they themselves provide

► Examples: ▸ Facebook combining PII from logged-in users with website data from

outside Facebook▸ Google adding more ways to collect, but sharing less (keyword phrases)▸ Twitter using MoPub’s mobile advertising network in connection with PII

from logged in users to customise ads and track users across devices

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Online players should know the pros and cons of working with data monopolists

► Value-add from Social Graph, Google Analytics, App Store etc. has become indispensable

► Lock-in via hardware or membership is strong

► Make no mistake:Access to Walled Gardens is not ‘free’▸ Monetization monopoly (provider tax and unregulated pricing)▸ Penalties for (alleged) misuse, no neutral jurisdiction▸ Business risks when models and terms change▸ Unpredictability and lack of partnership options

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Wiggle rooms in technology and compliance need to be understood, but risk of arbitrary changes remains

► Tactics to minimize dependency and mitigate risks:▸ Play by the rules (Options when rules change: 0)▸ Use technical loop-holes (which, even if working, may still cause violation

of terms and lead to penalties)▸ Externalize technology (minimize data exchange, build up proprietary

technology for data collection and aggregation)▸ Use conceptual loop-holes (move activity into ‘free zone’ of Walled

Garden or outside of it, e.g. mobile browser instead of native app)

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Consequences from clashes with big players are devastating, and many participants can be affected

► When things go south:▸ HasOffers and Kontagent banned from Facebook Ad Exchange for

holding on to anonymous Facebook data for too long▸ Apple banning apps which promote other apps, let users earn rewards

for watching videos, social sharing▸ Google: forward-integrating into publisher verticals like travel search,

local search, ratings, reviews

► Small changes of monopolists can cause ripple effects in entire value chain

3) PLATFORM-TO-PLATFORMEXAMPLES AND TAKE-AWAYS


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Data exchange focuses on tracing single transactionsData sharing (forward and backward) is underdeveloped

Traffic Source

•Publishers aggregate traffic•SEO, SEA, Social Media, E-Mail, Display, direct partnerships …•Profiles are created•Click-Out

Publisher

•Click-In•Multiple interactions •Unrelated to specific advertiser

•Personalisation (optional)

•Click-Out

Tracking Intermedi

ary

•Multiple interactions before conversion•Many potential advertisers per user•Profiling via cookie, session and fingerprint•Redirect

Advertiser

•Click-In•User interaction geared towards purchase•Personalisation (PII)•Transaction•Call-Back•Post-Transaction

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TO DO: Advertisers

► Share activities not leading to

conversion

▸ ‘Add to basket’ and other

conversion targets before

purchase

▸ Return visits

▸ Recurring customer

▸ Session time

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TO DO: Advertisers

► Store user-specific publisher

ID in ERP/CRM Enable

post-transaction cooperations

and customer life-time

feedback

► Share (aggregated)

demographic data to improve

targeting capabilities of

publishers

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TO DO: Advertisers

► Provide structured

cancellation reasons

► Provide anonymised and non-

PII data (payment method,

basket value, zip code,

gender, age group)

► Adapt landingpages and

check-out process

to traffic and user profiles

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TO DO: Publishers

► Use multi-level Sub-

IDs: Track and

optimize outgoing

traffic for various

parameters

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TO DO: Publishers

► Share user activity data with

advertisers:

▸ Recurring or frequent user,

readiness to buy, other

products and categories

▸ Depth and type of click-out

(detailed review vs. start page

promotional link, interest in

brand, price, promotion or

features)

▸ Personalized user which can

be retargeted by publisher

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TO DO: Publishers

► Upgrade technology to receive and

process advertiser data:

▸ Realtime-tracking of conversions:

calculate gross ROI and rankings

▸ Processing of cancellations to

calculate net ROI

▸ Reception of non-paying

conversion targets to retarget

users and optimize content

▸ Demographic information to

improve relevance of content and

targeting

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TO DO: Tracking Intermediaries

► Provide maximum

openness in data

collection, aggregation and

exchange

► Support all technical

industry standards for data

exports and APIs

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TO DO: Tracking Intermediaries

► Define meaningful data

structure for all relevant

Online-Marketing and e-

Commerce parameters

► Allow advertisers and

publishers to define privacy

settings for each shared

parameter (private hash

value clear value)

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Data-sharing principles

► Sharing meaningful data along the value chain creates new business cycles

► Deeper integration into each other’s business yields stronger partnerships

► Data privacy and compliance standards are essential to uphold

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Data-sharing principles

► AggregateAnonymize data by aggregating it in meaningful segments before sharing it

► Use hash valuesPII and internal parameters can be exchanged by creating hash values which are stored in both systems

► Enhance data storage capabilities▸ Incorporate hashed or anonymised information into your own data

structure▸ Reserve space for 3rd party data in different formats▸ Create shared pools of information which can be used to increase quality

of advertising

THANK YOU

Robert Schneider (COO)

@IngeniousTechAG

APPENDIX: DATA TOOLS


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Common data tools store, aggregate and provide information

Tag Management Container script tools to manage all on-page tracking tags- and pixels and define deduplication rules and conditions

Web Analytics Free and commercial tools to collect, aggregate and analyze off-page and on-page metrics of websites

Tracking and Private Network Solutions

Tools to measure, register and rate all tracking events across multiple channels according to a set of predefined rules and attribution models

Campaign management platforms

Proprietary tools of advertising platforms (e.g. Search or Display marketing) used for targeting, relevance and budget control

Affiliate Networks Platforms connecting advertisers and publishers using tracking technologyeCommerce Systems Platforms providing front-end and back-end tools for Online-Shops, including product

management and customer management modulesData Warehouse Solution to store big data from all sources in a unified format